Merge pull request #619 from nouiz/install

doc/install.txt

@@ -76,6 +76,16 @@ The following libraries and software are optional:
 Linux
 -----
 
+CentOS 6
+~~~~~~~~
+
+:ref:`install_centos6` provides instructions on how to install Theano on CentOS
+6, written by the Theano developers. It covers how to install Theano (for
+CPU-based computation only) with the distribution-packaged ATLAS, a free fast
+implementation of BLAS.
+
+.. Cent OS 6
+
 Alternative installation on Ubuntu with PPA
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -83,13 +93,20 @@ Benjamin J. McCann provides `installation documentation
 <http://www.benmccann.com/dev-blog/installing-cuda-and-theano/>`_ for
 Ubuntu 11.04 with CUDA 4.0 PPA.
 
-Gentoo
-~~~~~~
+Alternative installation on Gentoo
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Brian Vandenberg emailed `installation instructions on Gentoo
 <http://groups.google.com/d/msg/theano-dev/-8WCMn2FMR0/bJPasoZXaqoJ>`_,
 focusing on how to install the appropriate dependencies.
 
+Alternative installation on Mandriva 2010.2
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+A contributor made rpm package for Mandriva_ 2010.2 of Theano 0.3.1.
+
+.. _Mandriva: http://mib.pianetalinux.org/mib/quick/basic-rpms/mib-rpms/975-theano-031
+
 
 .. _linux_basic:
 
@@ -144,12 +161,38 @@ directory; see the `virtualenv documentation`_ for details.
 
 .. _install_bleeding_edge:
 
-With rpm package
-~~~~~~~~~~~~~~~~
+Updating Theano
+~~~~~~~~~~~~~~~
 
-A contributor made rpm package for Mandriva_ 2010.2 of Theano 0.3.1.
+The following command will update only Theano:
+
+.. code-block:: bash
+
+    sudo pip install --upgrade --no-deps theano
+
+The following command will update Theano and Numpy/Scipy (warning bellow):
+
+.. code-block:: bash
+
+    sudo pip install --upgrade theano
+
+
+If you installed NumPy/SciPy with yum/apt-get, updating NumPy/SciPy
+with pip/easy_install is not always a good idea. This can make Theano
+crash due to problems with BLAS (but see below). The versions of
+NumPy/SciPy in the distribution are sometimes linked against faster
+versions of BLAS. Installing NumPy/SciPy with
+yum/apt-get/pip/easy_install won't install the development package
+needed to recompile it with the fast version. This mean that if you
+don't install the development packages manually, when you recompile
+the updated NumPy/SciPy, it will compile with the slower version. This
+results in a slower Theano as well. To fix the crash, you can clear
+the Theano cache like this:
+
+.. code-block:: bash
+
+    theano-cache clear
 
-.. _Mandriva: http://mib.pianetalinux.org/mib/quick/basic-rpms/mib-rpms/975-theano-031
 
 Bleeding-edge install instructions
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

doc/install_centos6.txt

+
+.. _install_centos6:
+
+
+Easy Installation of an optimized Theano on CentOS 6
+====================================================
+
+.. note::
+
+    It is possible to have a faster installation of Theano than the one these
+    instructions will provide, but this will make the installation more
+    complicated and/or may require that you buy software. This is a simple set
+    of installation instructions that will leave you with a relatively
+    well-optimized version that uses only free software. With more work or by
+    investing money (i.e. buying a license to a proprietary BLAS
+    implementation), it is possible to gain further performance.
+
+.. note::
+
+    These instructions will result in Theano using only 1 thread for all BLAS
+    function calls. See the note above; other BLAS implementations can employ
+    multithreading to speed up computation.
+
+.. note::
+
+   If you are behind a proxy, you must do some extra configuration steps
+   before starting the installation. You must set the environment
+   variable ``http_proxy`` to the proxy address. Using bash this is
+   accomplished with the command
+   ``export http_proxy="http://user:pass@my.site:port/"``
+   You can also provide the ``--proxy=[user:pass@]url:port`` parameter
+   to pip. The ``[user:pass@]`` portion is optional.
+
+.. note::
+
+   We use ``pip`` for 2 reasons. First, it allows "``import module;
+   module.test()``" to work correctly. Second, the installation of NumPy
+   1.6 or 1.6.1 with ``easy_install`` raises an ImportError at the end of
+   the installation. To my knowledge we can ignore this error, but
+   this is not completely safe. ``easy_install`` with NumPy 1.5.1 does not
+   raise this error.
+
+
+
+Installation steps
+~~~~~~~~~~~~~~~~~~
+
+ 1) ``sudo yum install python-devel python-nose python-setuptools gcc
+    gcc-gfortran gcc-c++ blas-devel lapack-devel atlas-devel``
+ 2) ``sudo easy_install pip``
+ 3) ``sudo pip install numpy==1.6.1``
+ 4) ``sudo pip install scipy==0.10.1``
+ 5) ``sudo pip install Theano``
+
+
+Test the newly installed packages
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+ 1) NumPy (~30s): ``python -c "import numpy; numpy.test()"``
+ 2) SciPy (~1m): ``python -c "import scipy; scipy.test()"``
+ 3) Theano (~30m): ``python -c "import theano; theano.test()"``
+
+
+Speed test Theano/BLAS
+~~~~~~~~~~~~~~~~~~~~~~
+
+It is recommended to test your Theano/BLAS integration. There are many versions
+of BLAS that exist and there can be up to 10x speed difference between them.
+Also, having Theano link directly against BLAS instead of using NumPy/SciPy as
+an intermediate layer reduces the computational overhead. This is
+important for BLAS calls to ``ger``, ``gemv`` and small ``gemm`` operations
+(automatically called when needed when you use ``dot()``). To run the
+Theano/BLAS speed test:
+
+.. code-block:: bash
+
+    python /usr/lib/python2.*/site-packages/theano/misc/check_blas.py
+
+This will print a table with different versions of BLAS/numbers of
+threads on multiple CPUs and GPUs. It will also print some Theano/NumPy
+configuration information. Then, it will print the running time of the same
+benchmarks for your installation. Try to find a CPU similar to yours in
+the table, and check that the single-threaded timings are roughly the same.
+
+
+Updating Theano
+~~~~~~~~~~~~~~~
+
+If you followed these installation instructions, you can execute this command
+to update only Theano:
+
+.. code-block:: bash
+
+    sudo pip install --upgrade --no-deps theano
+
+
+If you want to also update NumPy/SciPy, you can run this:
+
+.. code-block:: bash
+
+    sudo pip install --upgrade theano
+